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* Author: Eitan Marder-Eppstein
*********************************************************************/
#ifndef DWA_LOCAL_PLANNER_VELOCITY_ITERATOR_H_
#define DWA_LOCAL_PLANNER_VELOCITY_ITERATOR_H_

#include <algorithm>
#include <cmath>
#include <vector>

namespace base_local_planner
{

/** VelocityIterator用于获得相同大小的最大和最小值
 * We use the class to get even sized samples between min and max, inluding zero if it is not included (and range goes from negative to positive
 */
class VelocityIterator
{
public:
    VelocityIterator(double min, double max, int num_samples) :
            current_index(0)
    {
        if (min == max) samples_.push_back(min);
        else
        {
            num_samples = std::max(2, num_samples);
            // e.g. for 4 samples, split distance in 3 even parts
            double step_size = (max - min) / double(std::max(1, (num_samples - 1)));
            // we make sure to avoid rounding errors around min and max.
            double current;
            double next = min;
            for (int j = 0; j < num_samples - 1; ++j)
            {
                current = next;
                next += step_size;
                samples_.push_back(current);
                // if 0 is among samples, this is never true. Else it inserts a 0 between the positive and negative samples
                if ((current < 0) && (next > 0)) samples_.push_back(0.0);
            }
            samples_.push_back(max);
        }
    }
    double getVelocity() { return samples_.at(current_index); }

    VelocityIterator &operator++(int)
    {
        current_index++;
        return *this;
    }

    void reset() { current_index = 0; }

    bool isFinished() { return current_index >= samples_.size(); }

private:
    std::vector<double> samples_;
    unsigned int current_index;
};
};
#endif
